Project DetailsDevelopmental disorders are a group of neurological conditions originating at childhood, that involve serious impairments in various areas (language, learning, motor skills). These conditions also comprise Autism Spectrum Disorders. As of 2008, approximately 15% of children in the United States have been diagnosed with some sort of developmental disorder, is comparison to only 12.8% in 1997 [1]. Early detection of developmental disorders is crucial, as it enables early intervention (e.g. speech therapist, occupational therapy), which may reduce neurological and functional deficits in infants.In this project we have developed a tool for an early identification of developmental disorders in infants. The tool exploits the correlation between acoustical features of an infants cry (e.g. pitch and formants) and the risk of having developmental disorders. We have used digital signal processing tools to characterize the input cry signals, and a k-NN based machine learning system to estimate the infants risk of having a developmental disorder. The tool has been tested against a database of diagnosed infants, and produced 85% success in estimating developmental disorders in infants in cross-validation testing.
